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<title>Compute Library: ICLKernel Class Reference</title>
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<a href="#pub-methods">Public Member Functions</a> &#124;
<a href="#pub-static-methods">Static Public Member Functions</a>  </div>
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<div class="title">ICLKernel Class Reference<span class="mlabels"><span class="mlabel">abstract</span></span></div>  </div>
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<p>Common interface for all the OpenCL kernels.  
 <a href="classarm__compute_1_1_i_c_l_kernel.xhtml#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>&gt;</code></p>
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Collaboration diagram for ICLKernel:</div>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a6b10e96ce90bf901d17def86b874b019"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6b10e96ce90bf901d17def86b874b019">ICLKernel</a> ()</td></tr>
<tr class="memdesc:a6b10e96ce90bf901d17def86b874b019"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="#a6b10e96ce90bf901d17def86b874b019">More...</a><br /></td></tr>
<tr class="separator:a6b10e96ce90bf901d17def86b874b019"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae5121015ab09ece4d470f50c7ffe198e"><td class="memItemLeft" align="right" valign="top">cl::Kernel &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ae5121015ab09ece4d470f50c7ffe198e">kernel</a> ()</td></tr>
<tr class="memdesc:ae5121015ab09ece4d470f50c7ffe198e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns a reference to the OpenCL kernel of this object.  <a href="#ae5121015ab09ece4d470f50c7ffe198e">More...</a><br /></td></tr>
<tr class="separator:ae5121015ab09ece4d470f50c7ffe198e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9331d385192a50adf74d3af40ce0fa20"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a9331d385192a50adf74d3af40ce0fa20"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a9331d385192a50adf74d3af40ce0fa20">add_1D_array_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *array, const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;strides, unsigned int num_dimensions, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a9331d385192a50adf74d3af40ce0fa20"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx.  <a href="#a9331d385192a50adf74d3af40ce0fa20">More...</a><br /></td></tr>
<tr class="separator:a9331d385192a50adf74d3af40ce0fa20"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a479e7043e65dc87de35d374e108510f7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">add_1D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a479e7043e65dc87de35d374e108510f7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.  <a href="#a479e7043e65dc87de35d374e108510f7">More...</a><br /></td></tr>
<tr class="separator:a479e7043e65dc87de35d374e108510f7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac74dad3e61f79334f5e73f3c3ac603cb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:ac74dad3e61f79334f5e73f3c3ac603cb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.  <a href="#ac74dad3e61f79334f5e73f3c3ac603cb">More...</a><br /></td></tr>
<tr class="separator:ac74dad3e61f79334f5e73f3c3ac603cb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a28f5847162f352444c6ac1825d0e99c7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">add_3D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a28f5847162f352444c6ac1825d0e99c7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx.  <a href="#a28f5847162f352444c6ac1825d0e99c7">More...</a><br /></td></tr>
<tr class="separator:a28f5847162f352444c6ac1825d0e99c7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a33e09c946b338fbfc780a9d1c66e68ad"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a33e09c946b338fbfc780a9d1c66e68ad">add_4D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a33e09c946b338fbfc780a9d1c66e68ad"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx.  <a href="#a33e09c946b338fbfc780a9d1c66e68ad">More...</a><br /></td></tr>
<tr class="separator:a33e09c946b338fbfc780a9d1c66e68ad"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af6a174d47571f51f199ffc27ecc10f51"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#af6a174d47571f51f199ffc27ecc10f51">run</a> (const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>, cl::CommandQueue &amp;queue)=0</td></tr>
<tr class="memdesc:af6a174d47571f51f199ffc27ecc10f51"><td class="mdescLeft">&#160;</td><td class="mdescRight">Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.  <a href="#af6a174d47571f51f199ffc27ecc10f51">More...</a><br /></td></tr>
<tr class="separator:af6a174d47571f51f199ffc27ecc10f51"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a50f427a1d9419800972b9e03c4034311"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a50f427a1d9419800972b9e03c4034311"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a50f427a1d9419800972b9e03c4034311">add_argument</a> (unsigned int &amp;idx, T value)</td></tr>
<tr class="memdesc:a50f427a1d9419800972b9e03c4034311"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed parameters to the object's kernel's arguments starting from the index idx.  <a href="#a50f427a1d9419800972b9e03c4034311">More...</a><br /></td></tr>
<tr class="separator:a50f427a1d9419800972b9e03c4034311"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad356b88c8f61267d593d9ed99835bde9"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad356b88c8f61267d593d9ed99835bde9">set_lws_hint</a> (const cl::NDRange &amp;<a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a0737b867334392d5dc5c2e3291d67dbf">lws_hint</a>)</td></tr>
<tr class="memdesc:ad356b88c8f61267d593d9ed99835bde9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the Local-Workgroup-Size hint.  <a href="#ad356b88c8f61267d593d9ed99835bde9">More...</a><br /></td></tr>
<tr class="separator:ad356b88c8f61267d593d9ed99835bde9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0737b867334392d5dc5c2e3291d67dbf"><td class="memItemLeft" align="right" valign="top">cl::NDRange&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a0737b867334392d5dc5c2e3291d67dbf">lws_hint</a> () const </td></tr>
<tr class="memdesc:a0737b867334392d5dc5c2e3291d67dbf"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return the Local-Workgroup-Size hint.  <a href="#a0737b867334392d5dc5c2e3291d67dbf">More...</a><br /></td></tr>
<tr class="separator:a0737b867334392d5dc5c2e3291d67dbf"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a226d2e9e6d3c42d681666566fe950b2d"><td class="memItemLeft" align="right" valign="top">const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a226d2e9e6d3c42d681666566fe950b2d">config_id</a> () const </td></tr>
<tr class="memdesc:a226d2e9e6d3c42d681666566fe950b2d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the configuration ID.  <a href="#a226d2e9e6d3c42d681666566fe950b2d">More...</a><br /></td></tr>
<tr class="separator:a226d2e9e6d3c42d681666566fe950b2d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad5ba9d34a3a855bf1dd2e36316ff550a"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad5ba9d34a3a855bf1dd2e36316ff550a">set_target</a> (<a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> target)</td></tr>
<tr class="memdesc:ad5ba9d34a3a855bf1dd2e36316ff550a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the targeted GPU architecture.  <a href="#ad5ba9d34a3a855bf1dd2e36316ff550a">More...</a><br /></td></tr>
<tr class="separator:ad5ba9d34a3a855bf1dd2e36316ff550a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a57e5f498fcbfc25c28b8496dfa3fc33c"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a57e5f498fcbfc25c28b8496dfa3fc33c">set_target</a> (cl::Device &amp;device)</td></tr>
<tr class="memdesc:a57e5f498fcbfc25c28b8496dfa3fc33c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the targeted GPU architecture according to the CL device.  <a href="#a57e5f498fcbfc25c28b8496dfa3fc33c">More...</a><br /></td></tr>
<tr class="separator:a57e5f498fcbfc25c28b8496dfa3fc33c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a646cd535a16835b246c3367a63d96250"><td class="memItemLeft" align="right" valign="top"><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a646cd535a16835b246c3367a63d96250">get_target</a> () const </td></tr>
<tr class="memdesc:a646cd535a16835b246c3367a63d96250"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the targeted GPU architecture.  <a href="#a646cd535a16835b246c3367a63d96250">More...</a><br /></td></tr>
<tr class="separator:a646cd535a16835b246c3367a63d96250"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abca336f832d730e8494049bd714df60a"><td class="memItemLeft" align="right" valign="top">size_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#abca336f832d730e8494049bd714df60a">get_max_workgroup_size</a> ()</td></tr>
<tr class="memdesc:abca336f832d730e8494049bd714df60a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the maximum workgroup size for the device the <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> uses.  <a href="#abca336f832d730e8494049bd714df60a">More...</a><br /></td></tr>
<tr class="separator:abca336f832d730e8494049bd714df60a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2d7c6b5f3332604ad6a637457f65c342"><td class="memTemplParams" colspan="2">template&lt;typename T , unsigned int dimension_size&gt; </td></tr>
<tr class="memitem:a2d7c6b5f3332604ad6a637457f65c342"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a2d7c6b5f3332604ad6a637457f65c342">add_array_argument</a> (unsigned &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *array, const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;strides, unsigned int num_dimensions, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a2d7c6b5f3332604ad6a637457f65c342"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed array's parameters to the object's kernel's arguments starting from the index idx.  <a href="#a2d7c6b5f3332604ad6a637457f65c342">More...</a><br /></td></tr>
<tr class="separator:a2d7c6b5f3332604ad6a637457f65c342"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classarm__compute_1_1_i_kernel"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_kernel')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_kernel.xhtml">IKernel</a></td></tr>
<tr class="memitem:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a7250cb8cbaa4104a93a2d77155085507">IKernel</a> ()</td></tr>
<tr class="memdesc:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="#a7250cb8cbaa4104a93a2d77155085507">More...</a><br /></td></tr>
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<tr class="memitem:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a341b60d15a5e12a5b8f3825194dd3b12">~IKernel</a> ()=default</td></tr>
<tr class="memdesc:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor.  <a href="#a341b60d15a5e12a5b8f3825194dd3b12">More...</a><br /></td></tr>
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<tr class="memitem:abfab8f0d4928e1081d9f65b77933e24a inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#abfab8f0d4928e1081d9f65b77933e24a">is_parallelisable</a> () const </td></tr>
<tr class="memdesc:abfab8f0d4928e1081d9f65b77933e24a inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Indicates whether or not the kernel is parallelisable.  <a href="#abfab8f0d4928e1081d9f65b77933e24a">More...</a><br /></td></tr>
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<tr class="memitem:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#aa6daa9b04e2035bf007e5e5c3c4396a8">border_size</a> () const </td></tr>
<tr class="memdesc:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">The size of the border for that kernel.  <a href="#aa6daa9b04e2035bf007e5e5c3c4396a8">More...</a><br /></td></tr>
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<tr class="memitem:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a> () const </td></tr>
<tr class="memdesc:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum window the kernel can be executed on.  <a href="#a3f5646133956f06348b310ccc3d36353">More...</a><br /></td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:a278f0e6c68ca17e71f4c4ff82f360aa0"><td class="memItemLeft" align="right" valign="top">static constexpr unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a278f0e6c68ca17e71f4c4ff82f360aa0">num_arguments_per_1D_array</a> ()</td></tr>
<tr class="memdesc:a278f0e6c68ca17e71f4c4ff82f360aa0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 1D array object.  <a href="#a278f0e6c68ca17e71f4c4ff82f360aa0">More...</a><br /></td></tr>
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<tr class="memitem:a43b6c5e4b57069c5f61e96dff24c212d"><td class="memItemLeft" align="right" valign="top">static constexpr unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a43b6c5e4b57069c5f61e96dff24c212d">num_arguments_per_1D_tensor</a> ()</td></tr>
<tr class="memdesc:a43b6c5e4b57069c5f61e96dff24c212d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 1D tensor object.  <a href="#a43b6c5e4b57069c5f61e96dff24c212d">More...</a><br /></td></tr>
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<tr class="memitem:a45601e0d46621a5b6f2e417d60e5c800"><td class="memItemLeft" align="right" valign="top">static constexpr unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800">num_arguments_per_2D_tensor</a> ()</td></tr>
<tr class="memdesc:a45601e0d46621a5b6f2e417d60e5c800"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 2D tensor object.  <a href="#a45601e0d46621a5b6f2e417d60e5c800">More...</a><br /></td></tr>
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<tr class="memitem:a6c9c1e7a7d96743375ca40847f0f12e2"><td class="memItemLeft" align="right" valign="top">static constexpr unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2">num_arguments_per_3D_tensor</a> ()</td></tr>
<tr class="memdesc:a6c9c1e7a7d96743375ca40847f0f12e2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 3D tensor object.  <a href="#a6c9c1e7a7d96743375ca40847f0f12e2">More...</a><br /></td></tr>
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<tr class="memitem:a184fdf37587a9314cf12623accea6c73"><td class="memItemLeft" align="right" valign="top">static constexpr unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a184fdf37587a9314cf12623accea6c73">num_arguments_per_4D_tensor</a> ()</td></tr>
<tr class="memdesc:a184fdf37587a9314cf12623accea6c73"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 4D tensor object.  <a href="#a184fdf37587a9314cf12623accea6c73">More...</a><br /></td></tr>
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<tr class="memitem:a4b4a20e518c04e657839280cd486a85d"><td class="memItemLeft" align="right" valign="top">static cl::NDRange&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a4b4a20e518c04e657839280cd486a85d">gws_from_window</a> (const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a4b4a20e518c04e657839280cd486a85d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the global work size given an execution window.  <a href="#a4b4a20e518c04e657839280cd486a85d">More...</a><br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Common interface for all the OpenCL kernels. </p>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00043">43</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
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          <td class="memname"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml">ICLKernel</a> </td>
          <td>(</td>
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<p>Constructor. </p>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00067">67</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        : _kernel(<span class="keyword">nullptr</span>), _lws_hint(<a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#aebe2d25607545d31f2b1ace6d60a81da">CLKernelLibrary::get</a>().default_ndrange()), _target(<a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38">GPUTarget::MIDGARD</a>), _config_id(arm_compute::default_config_id), _max_workgroup_size(0)</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    {</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_c_l_kernel_library_xhtml_aebe2d25607545d31f2b1ace6d60a81da"><div class="ttname"><a href="classarm__compute_1_1_c_l_kernel_library.xhtml#aebe2d25607545d31f2b1ace6d60a81da">arm_compute::CLKernelLibrary::get</a></div><div class="ttdeci">static CLKernelLibrary &amp; get()</div><div class="ttdoc">Access the KernelLibrary singleton. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38">arm_compute::GPUTarget::MIDGARD</a></div></div>
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<h2 class="groupheader">Member Function Documentation</h2>
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          <td class="memname">void add_1D_array_argument </td>
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          <td class="paramtype">unsigned int &amp;&#160;</td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *&#160;</td>
          <td class="paramname"><em>array</em>, </td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;&#160;</td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
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<p>Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">array</td><td><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> to set as an argument of the object's kernel. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">strides</td><td><a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> object containing stride of each dimension in bytes. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">num_dimensions</td><td>Number of dimensions of the <code>array</code>. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00088">88</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    {</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        add_array_argument&lt;T, 1&gt;(idx, array, strides, num_dimensions, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
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          <td class="memname">void add_1D_tensor_argument </td>
          <td>(</td>
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          <td class="paramkey"></td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
          <td class="paramname"><em>tensor</em>, </td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
          <td class="paramname"><em>window</em>&#160;</td>
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<p>Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00098">98</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    {</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        add_tensor_argument&lt;1&gt;(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
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          <td class="memname">void add_2D_tensor_argument </td>
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          <td class="paramname"><em>idx</em>, </td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
          <td class="paramname"><em>tensor</em>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
          <td class="paramname"><em>window</em>&#160;</td>
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<p>Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00108">108</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    {</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        add_tensor_argument&lt;2&gt;(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>);</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
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          <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
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<p>Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
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    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00118">118</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    {</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;        add_tensor_argument&lt;3&gt;(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>);</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
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<p>Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
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    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00128">128</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    {</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        add_tensor_argument&lt;4&gt;(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>);</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
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<p>Add the passed parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
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    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the arguments. Will be incremented by the number of kernel arguments set. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00186">186</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    {</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        _kernel.setArg(idx++, value);</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    }</div></div><!-- fragment -->
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<p>Add the passed array's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">array</td><td><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> to set as an argument of the object's kernel. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">strides</td><td><a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> object containing stride of each dimension in bytes. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">num_dimensions</td><td>Number of dimensions of the <code>array</code>. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00315">315</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="_error_8h_source.xhtml#l00328">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_error_8h_source.xhtml#l00319">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="_error_8h_source.xhtml#l00159">ARM_COMPUTE_UNUSED</a>, and <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml#a1fb4c50755a0ef424652246838ed91a6">ICLArray&lt; T &gt;::cl_buffer()</a>.</p>
<div class="fragment"><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;{</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;    <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(array == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;</div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    <span class="comment">// Calculate offset to the start of the window</span></div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> offset_first_element = 0;</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n &lt; num_dimensions; ++n)</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    {</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;        offset_first_element += <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>[n].start() * strides[n];</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    }</div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx_start = idx;</div><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    _kernel.setArg(idx++, array-&gt;cl_buffer());</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension = 0; dimension &lt; dimension_size; dimension++)</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    {</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;        _kernel.setArg&lt;cl_uint&gt;(idx++, strides[dimension]);</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;        _kernel.setArg&lt;cl_uint&gt;(idx++, strides[dimension] * <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>[dimension].step());</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    }</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    _kernel.setArg&lt;cl_uint&gt;(idx++, offset_first_element);</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;    <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(idx_start + num_arguments_per_array&lt;dimension_size&gt;() != idx,</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;                             <span class="stringliteral">&quot;add_%dD_array_argument() is supposed to add exactly %d arguments to the kernel&quot;</span>, dimension_size, num_arguments_per_array&lt;dimension_size&gt;());</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(idx_start);</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;}</div><div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00328">Error.h:328</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00159">Error.h:159</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
<div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00319">Error.h:319</a></div></div>
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<p>Get the configuration ID. </p>
<dl class="section note"><dt>Note</dt><dd>The configuration ID can be used by the caller to distinguish different calls of the same OpenCL kernel In particular, this method can be used by <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue. ">CLScheduler</a> to keep track of the best LWS for each configuration of the same kernel. The configuration ID should be provided only for the kernels potentially affected by the LWS geometry</dd>
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This method should be called after the configuration of the kernel</dd></dl>
<dl class="section return"><dt>Returns</dt><dd>configuration id string </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00221">221</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
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<p>Get the maximum workgroup size for the device the <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> uses. </p>
<dl class="section return"><dt>Returns</dt><dd>The maximum workgroup size value. </dd></dl>

<p>Referenced by <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00245">ICLKernel::get_target()</a>.</p>

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<p>Get the targeted GPU architecture. </p>
<dl class="section return"><dt>Returns</dt><dd>The targeted GPU architecture. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00245">245</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="namespacearm__compute.xhtml#a0f68015f649819f1102aa73d7b88b29e">arm_compute::enqueue()</a>, <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml#aebe2d25607545d31f2b1ace6d60a81da">CLKernelLibrary::get()</a>, <a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#abca336f832d730e8494049bd714df60a">ICLKernel::get_max_workgroup_size()</a>, <a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a4b4a20e518c04e657839280cd486a85d">ICLKernel::gws_from_window()</a>, <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00075">ICLKernel::kernel()</a>, <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00206">ICLKernel::lws_hint()</a>, and <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    {</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;        <span class="keywordflow">return</span> _target;</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    }</div></div><!-- fragment -->
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<p>Get the global work size given an execution window. </p>
<dl class="params"><dt>Parameters</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td>Execution window</td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Global work size of the given execution window </dd></dl>

<p>Referenced by <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00245">ICLKernel::get_target()</a>.</p>

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<p>Returns a reference to the OpenCL kernel of this object. </p>
<dl class="section return"><dt>Returns</dt><dd>A reference to the OpenCL kernel of this object. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00075">75</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>Referenced by <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00245">ICLKernel::get_target()</a>.</p>
<div class="fragment"><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    {</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        <span class="keywordflow">return</span> _kernel;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    }</div></div><!-- fragment -->
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<p>Return the Local-Workgroup-Size hint. </p>
<dl class="section return"><dt>Returns</dt><dd>Current lws hint </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00206">206</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>Referenced by <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00245">ICLKernel::get_target()</a>, <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00197">ICLKernel::set_lws_hint()</a>, and <a class="el" href="_tuner_8cpp_source.xhtml#l00044">arm_compute::test::validation::TEST_CASE()</a>.</p>
<div class="fragment"><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    {</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        <span class="keywordflow">return</span> _lws_hint;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    }</div></div><!-- fragment -->
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<p>Returns the number of arguments enqueued per 1D array object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 1D array object. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00136">136</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    {</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        <span class="keywordflow">return</span> num_arguments_per_array&lt;1&gt;();</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    }</div></div><!-- fragment -->
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<p>Returns the number of arguments enqueued per 1D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 1D tensor object. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00144">144</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    {</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        <span class="keywordflow">return</span> num_arguments_per_tensor&lt;1&gt;();</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    }</div></div><!-- fragment -->
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<p>Returns the number of arguments enqueued per 2D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 2D tensor object. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00152">152</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    {</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        <span class="keywordflow">return</span> num_arguments_per_tensor&lt;2&gt;();</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    }</div></div><!-- fragment -->
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<p>Returns the number of arguments enqueued per 3D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 3D tensor object. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00160">160</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    {</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        <span class="keywordflow">return</span> num_arguments_per_tensor&lt;3&gt;();</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    }</div></div><!-- fragment -->
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<p>Returns the number of arguments enqueued per 4D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 4D tensor object. </dd></dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00168">168</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#af6a174d47571f51f199ffc27ecc10f51">ICLKernel::run()</a>, and <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    {</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        <span class="keywordflow">return</span> num_arguments_per_tensor&lt;4&gt;();</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    }</div></div><!-- fragment -->
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<p>Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. </p>
<dl class="section note"><dt>Note</dt><dd>The queue is <em>not</em> flushed by this method, and therefore the kernel will not have been executed by the time this method returns.</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">window</td><td>Region on which to execute the kernel. (Must be a valid region of the window returned by <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a>). </td></tr>
    <tr><td class="paramdir">[in,out]</td><td class="paramname">queue</td><td>Command queue on which to enqueue the kernel. </td></tr>
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<p>Implemented in <a class="el" href="classarm__compute_1_1_c_l_logits1_d_norm_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLogits1DNormKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage1_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerStage1Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLConvolutionRectangleKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_logits1_d_max_shift_exp_sum_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLogits1DMaxShiftExpSumKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage0_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerStage0Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLEdgeTraceKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_b_reduction_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpMatrixBReductionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_finalize_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerFinalizeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_copy_to_array_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLCopyToArrayKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel5x5_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel5x5VertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel7x7_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel7x7VertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_h_o_g_block_normalization_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHOGBlockNormalizationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_im2_col_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLIm2ColKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_min_max_location_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMinMaxLocationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLEdgeNonMaxSuppressionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLWeightsReshapeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_init_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerInitKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGaussianPyramidVertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_histogram_border_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHistogramBorderKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_logits1_d_shift_exp_sum_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLogits1DShiftExpSumKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBatchNormalizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMTranspose1xWKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDirectConvolutionLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_col2_im_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLCol2ImKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_offset_contribution_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpOffsetContributionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_a_reduction_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpMatrixAReductionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMInterleave4x4Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLColorConvertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_im2_col_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseIm2ColKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpMatrixMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLL2NormalizeLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLPixelWiseMultiplicationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_output_stage_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDirectConvolutionLayerOutputStageKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_winograd_output_transform_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLWinogradOutputTransformKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLArithmeticSubtractionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_scharr3x3_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLScharr3x3Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_winograd_filter_transform_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLWinogradFilterTransformKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLArithmeticAdditionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLConvertFullyConnectedWeightsKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_reduction_operation_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLReductionOperationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLChannelCombineKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDequantizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector_kernel.xhtml#ac8f1ca778b425c6408a93b672b041dd0">CLHOGDetectorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLWinogradInputTransformKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_vector_to_tensor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseVectorToTensorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_harris_score_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHarrisScoreKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_min_max_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMinMaxLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLPoolingLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLQuantizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLWidthConcatenateLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLActivationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDeconvolutionLayerUpsampleKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_weights_reshape_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseWeightsReshapeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_fast_corners_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLFastCornersKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_addition_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixAdditionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLChannelExtractKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseConvolutionLayer3x3NCHWKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseConvolutionLayer3x3NHWCKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLFillBorderKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_locally_connected_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLocallyConnectedMatrixMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLNormalizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLPermuteKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLChannelShuffleLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_integral_image_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLIntegralImageVertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLROIPoolingLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthConcatenateLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_vector_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixVectorMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMagnitudePhaseKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_accumulate_biases_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixAccumulateBiasesKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMeanStdDevKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLAbsoluteDifferenceKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_h_o_g_orientation_binning_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHOGOrientationBinningKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel5x5_hor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel5x5HorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel7x7_hor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel7x7HorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_derivative_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDerivativeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel3x3_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel3x3Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBitwiseAndKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBitwiseOrKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBitwiseXorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_min_max_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMinMaxKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_remap_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLRemapKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGradientKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_histogram_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHistogramKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_hor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGaussianPyramidHorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLReshapeLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLFloorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_copy_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLCopyKernel</a>, <a class="el" href="classarm__compute_1_1_i_c_l_simple3_d_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">ICLSimple3DKernel</a>, and <a class="el" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">ICLSimple2DKernel</a>.</p>

<p>Referenced by <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00168">ICLKernel::num_arguments_per_4D_tensor()</a>.</p>

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          <td class="memname">void set_lws_hint </td>
          <td>(</td>
          <td class="paramtype">const cl::NDRange &amp;&#160;</td>
          <td class="paramname"><em>lws_hint</em></td><td>)</td>
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<p>Set the Local-Workgroup-Size hint. </p>
<dl class="section note"><dt>Note</dt><dd>This method should be called after the configuration of the kernel</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">lws_hint</td><td>Local-Workgroup-Size to use </td></tr>
  </table>
  </dd>
</dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00197">197</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>References <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00206">ICLKernel::lws_hint()</a>.</p>

<p>Referenced by <a class="el" href="_tuner_8cpp_source.xhtml#l00044">arm_compute::test::validation::TEST_CASE()</a>.</p>
<div class="fragment"><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    {</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;        _lws_hint = <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a0737b867334392d5dc5c2e3291d67dbf">lws_hint</a>;</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    }</div><div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a0737b867334392d5dc5c2e3291d67dbf"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a0737b867334392d5dc5c2e3291d67dbf">arm_compute::ICLKernel::lws_hint</a></div><div class="ttdeci">cl::NDRange lws_hint() const </div><div class="ttdoc">Return the Local-Workgroup-Size hint. </div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00206">ICLKernel.h:206</a></div></div>
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          <td class="memname">void set_target </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a>&#160;</td>
          <td class="paramname"><em>target</em></td><td>)</td>
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<p>Set the targeted GPU architecture. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">target</td><td>The targeted GPU architecture </td></tr>
  </table>
  </dd>
</dl>

<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00230">230</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>

<p>Referenced by <a class="el" href="_tuner_8cpp_source.xhtml#l00044">arm_compute::test::validation::TEST_CASE()</a>.</p>
<div class="fragment"><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    {</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;        _target = target;</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    }</div></div><!-- fragment -->
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          <td class="memname">void set_target </td>
          <td>(</td>
          <td class="paramtype">cl::Device &amp;&#160;</td>
          <td class="paramname"><em>device</em></td><td>)</td>
          <td></td>
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<p>Set the targeted GPU architecture according to the CL device. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">device</td><td>A CL device </td></tr>
  </table>
  </dd>
</dl>

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<hr/>The documentation for this class was generated from the following file:<ul>
<li>arm_compute/core/CL/<a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a></li>
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